11 citations · 69 across the 30 of their papers we have counts for
3 papers · 1 filter
P-Adapters: Robustly Extracting Factual Information from Language Models with Diverse Prompts
Benjamin Newman, Prafulla Kumar Choubey, Nazneen Rajani
Recent work (e.g. LAMA (Petroni et al., 2019)) has found that the quality of the factual information extracted from Large Language Models (LLMs) depends on the prompts used to quer…
CaPE: Contrastive Parameter Ensembling for Reducing Hallucination in Abstractive Summarization
Prafulla Kumar Choubey, Alexander R. Fabbri, Jesse Vig +3
Hallucination is a known issue for neural abstractive summarization models. Recent work suggests that the degree of hallucination may depend on errors in the training data. In this…
Improving Gender Translation Accuracy with Filtered Self-Training
Prafulla Kumar Choubey, Anna Currey, Prashant Mathur +1
Targeted evaluations have found that machine translation systems often output incorrect gender, even when the gender is clear from context. Furthermore, these incorrectly gendered…